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# create output data folder
mkdir_p(self.cfg.exp_path, self.cfg.params[self.cfg.opt_prnt])
if not self.cfg.cond_meta_file():
# automatic calibration data selection
obj = CaliFinder(self.cfg, self.sta)
ret = obj.main()
wht_img = obj.wht_bay[crop_h:-crop_h, crop_w:-crop_w] if obj.wht_bay is not None else obj.wht_bay
del obj
self.assertEqual(True, ret)
meta_cond = not (exists(self.cfg.params[self.cfg.cal_meta]) and self.cfg.params[self.cfg.cal_meta].lower().endswith('json'))
if meta_cond or self.cfg.params[self.cfg.opt_cali]:
# perform centroid calibration
obj = LfpCalibrator(wht_img, self.cfg, self.sta)
ret = obj.main()
self.cfg = obj.cfg
del obj
self.assertEqual(True, ret)
# load calibration data
self.cfg.load_cal_data()
# write centroids as png file
if wht_img is not None:
obj = CentroidDrawer(wht_img, self.cfg.calibs[self.cfg.mic_list], self.cfg)
ret = obj.write_centroids_img(fn='testcase_wht_img+mics.png')
del obj
self.assertEqual(True, ret)
if cal_opt:
# decode light field image
lfp_obj = lfp_reader.LfpReader(cfg)
lfp_obj.main()
lfp_img = lfp_obj.lfp_img[:, :-16]
del lfp_obj
# automatic calibration data selection
obj = lfp_calibrator.CaliFinder(cfg)
obj.main()
wht_img = obj.wht_bay[:, :-16]
del obj
if cal_opt:
# perform centroid calibration
cal_obj = lfp_calibrator.LfpCalibrator(wht_img, cfg)
cal_obj.main()
cfg = cal_obj.cfg
del cal_obj
else:
# convert Bayer to RGB representation
if len(wht_img.shape) == 2 and 'bay' in cfg.lfpimg:
# perform color filter array management and obtain rgb image
cfa_obj = CfaProcessor(bay_img=wht_img, cfg=cfg)
cfa_obj.bay2rgb()
wht_img = cfa_obj.rgb_img
del cfa_obj
# ensure white image is monochromatic
wht_img = rgb2gry(wht_img)[..., 0] if len(wht_img.shape) is 3 else wht_img
# load calibration data
def cal(self):
# perform centroid calibration
cal_obj = lfp_calibrator.LfpCalibrator(self.wht_img, self.cfg, self.sta)
cal_obj.main()
self.cfg = cal_obj.cfg
del cal_obj
if cfg.cond_auto_find():
# automatic calibration data selection
extractor = lfp_calibrator.CaliFinder(cfg, sta)
extractor.main()
wht_img = extractor.wht_bay
else:
# load white image calibration file
wht_img = misc.load_img_file(cfg.params[cfg.cal_path])
# save settings configuration
cfg.save_params()
# perform calibration if previously computed calibration data does not exist
meta_cond = not (os.path.exists(cfg.params[cfg.cal_meta]) and cfg.params[cfg.cal_meta].lower().endswith('json'))
if meta_cond or cfg.params[cfg.opt_cali]:
# perform centroid calibration
calibrator = lfp_calibrator.LfpCalibrator(wht_img, cfg, sta)
calibrator.main()
cfg = calibrator.cfg
# load calibration data
cfg.load_cal_data()
# check if light field alignment has been done before
if cfg.cond_lfp_align():
# align light field
aligner = lfp_aligner.LfpAligner(lfp_img, cfg, sta, wht_img)
aligner.main()
lfp_img_align = aligner.lfp_img
else:
lfp_img_align = None
# extract viewpoint data
def calibrate_folder(cfg, sta):
tarnames = [f for f in listdir(cfg.params[cfg.cal_path])
if isfile(join(cfg.params[cfg.cal_path], f)) and f.lower().endswith(".tar")]
for tarname in tarnames:
tar_obj = tarfile.open(tarname, mode='r')
for member in tar_obj.getmembers():
wht_img = tar_obj.extractfile(member)
LfpCalibrator(wht_img, cfg) #save metacalib.json
# check interrupt status
if sta.interrupt:
return False
return True